文章基本信息

标题：Automatic Road Extraction from High Resolution Satellite Images Using Neural Networks, Texture Analysis, Fuzzy Clustering and Genetic Algorithms
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作者：M. Mokhtarzade ; M. J. Valadan Zoej ; H. Ebadi 等
期刊名称：ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
印刷版ISSN：2194-9042
电子版ISSN：2194-9050
出版年度：2008
卷号：XXXVII Part B3b
页码：549-556
出版社：Copernicus Publications
摘要：In this article, a new method for road extraction from high resolution Quick Bird and IKONOS pan-sharpened satellite images is presented. The proposed methodology consists of two separate stages of road detection and road vectorization. Neural networks are applied on high resolution IKONOS and Quick-Bird images for road detection. This paper has endeavoured to optimize neural networks' functionality, using a variety of texture parameters. These texture parameters had different window sizes and grey level numbers, not only from source but also from pre-classified image. Road vectorization is based on the idea of road raster map clustering obtained from the previous road detection stage. In this step, despite of genetically guided clustering, a new flexible clustering methodology is proposed for road key point identification. The last step of road key point connecting is carried out based on the obtained information from a fuzzy shell based clustering. The accuracy assessment of the obtained vectorized road network proved the ability of the proposed method in sub-pixel road extraction
关键词：Road Extraction; Neural Networks; Co-occurrence Texture Analysis; Fuzzy Clustering; Vectorization